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University of California, San Francisco | San Francisco, California | United States | about 7 hours ago
education program learners. Coordinates program operations, which include teaching and learning activities, program curriculum, learner scheduling, and reporting education data, maintaining databases
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members. The faculty members are internationally recognized in research areas including power and energy systems, wireless and photonics systems, semiconductors, RF, and devices, AI and machine learning
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-Molecule Drug Discovery Strong foundation in computational methods (e.g. docking, molecular dynamics, QSAR, machine learning) Experience working across diverse target classes Demonstrated impact on
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simulations, machine learning and data analysis, and the opportunity to collaborate with experiments. This position would suit a researcher who has recently completed a PhD in Chemistry, Biochemistry
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instance, Machine Learning and AI, Big Data Analytics, Statistical Modeling, Data Visualization, Data Security, Cloud Computing, Applied Data Science in Healthcare and Environment, Data Engineering
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Interest in learning and strengthening existing skillsets Strong technical and programming skills, familiarity with current deep learning techniques, with a focus on computer vision Contact Information
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of this project will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The doctoral student position we
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national and international research networks. We are looking for someone with a PhD (or near completion) in a relevant field such as machine learning, biomedical engineering, or neuroscience, with expertise
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departments, and a thriving ecosystem of museums, libraries, and research centres. At Cambridge, our mission is to contribute to society through world-class education, learning, and research. With a deep
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1